RE: computer-go: Perl Module for next move.

["Fant, Chris" <chris.fant@xxxxxxxxxx>]

What's so hard about that?  If you don't want to do any reading to determine
the status of the remaining strings, can't you just use GOE rules?  Consider
all strings to be alive at the end of the game.  The network will have to
learn to remove dead strings from the board to before passing if it expects
to get credit for killing those stones.


-----Original Message-----
From: Grajdeanu, Adrian [mailto:adrian.grajdeanu@xxxxxxxxxxxxxxxxx]
Sent: Monday, June 04, 2001 11:28 AM
To: 'computer-go@xxxxxxxxxxxxxxxxx'
Subject: RE: computer-go: Perl Module for next move.


Very similar approach I had as well. Where I got somewhat stuck is when I
play two networks against each other and try to figure out the Go score. Did
you tackle this phase yet?

> -----Original Message-----
> From: Matthew Corey Brown [mailto:bromoc@xxxxxxxxxxxxxxxxx]
> Sent: Friday, 01 June, 2001 18:09
> To: 'computer-go@xxxxxxxxxxxxxxxxx'
> Subject: RE: computer-go: Perl Module for next move.
> 
> 
> A 3 layer(high node) neural network, The weights start off random, the
> inputs are the board locations, 0 for empty, 1 for your color 
> and -1 for
> the opponent. The output is one value the current score (Not go
> score, the score the net gives the board)  you take the orgional board
> position then go through all possible moves to find a higher 
> score. you
> take the highest score move and use that on your turn. No 
> higher scoor you
> either pass or not. You start with some number of nets with randomized
> values and have them all play eachother.. you total everyones 
> score (this
> time the Go score) then you take the top 50% scorers from that.. cross
> breed them using genteic algorythms, and then apply mutations 
> to each one.
>  repeat the prosses for a long time. And after 1000 
> generations or so the
> neural net may learn the game well enough.
> 
> would be interesting to see at which generation strategies 
> begin to form.
> 
> theres a checker player program that used around 800 nodes 
> and evolved the
> same way thats real good from what i understand after about 7 weeks of
> evolving on a pIII 400
> 
> 
> On Fri, 1 Jun 2001, Grajdeanu, Adrian wrote:
> 
> > Amaizingly, I want to do the same thing...
> > To analyze the table you use parts of the gnugo? If not, 
> how do you solve
> > it?
> > 
> > Adrian
> > 
> > 
> > > I'm interested in giving a function the current board, then 
> > > getting back
> > > an array of answers either the resulting borad after dead 
> peices are
> > > removed or an illeagle move. Perl is needed cause I have 
> a mishmash of
> > > computer architechures to use Genetic algorythms to 
> develop a neural
> > > network to determine the best move at that moment. I want 
> to watch the
> > > computer develop its own stratagems.
> > > 
> 
> Matthew Corey Brown                             
> bromoc@xxxxxxxxxxxxxxxxx 
>   "Death can not stop true love. All it can do is delay it 
> for awhile."
>